Underwater sonar imaging is a significant means for a variety of maritime work. However, the sonar images are corrupted by signal dependent speckle noise, which restricts the potential practical applications. In this paper, we propose a novel variational approach that addresses the adaptive sonar image denoising problem. To accurately describe the signal dependent characteristic of noise for real sensors, we utilize a generalized noise model, which can be adapted to represent various types of noise. With the generalized noise model, we formulate the denoising problem via a variational approach. Finally, we present a modified primal and dual method to efficiently solve the variational minimization problem. Experimental results on both simulated and real data validate the effectiveness and efficiency of our method.


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    Title :

    A variational approach for adaptive underwater sonar image denoising


    Contributors:
    Chen, Deshan (author) / Chu, Xiumin (author) / Ma, Feng (author) / Teng, XuanXuan (author)


    Publication date :

    2017-08-01


    Size :

    556393 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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